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Related Concept Videos

Autoimmune Disorders01:29

Autoimmune Disorders

686
Autoimmune diseases are a group of disorders in which the body's immune system mistakenly attacks its own cells, tissues, and organs. This results from an overactive immune response against substances and tissues normally present in the body. Let's delve into the concept and mechanism of autoimmune diseases from an immune system point of view, explore different causes and examples of such diseases, and discuss potential solutions.
Concept and Mechanism of Autoimmune Diseases
The immune...
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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Related Experiment Video

Updated: Sep 20, 2025

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
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Lessons From Transcriptome Analysis of Autoimmune Diseases.

Yasuo Nagafuchi1,2, Haruyuki Yanaoka3, Keishi Fujio1

  • 1Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Frontiers in Immunology
|June 6, 2022
PubMed
Summary

Transcriptome analysis reveals the specific roles of immune cells like monocytes, macrophages, T cells, and B cells in autoimmune diseases. This approach, including single-cell RNA sequencing, aids in understanding disease mechanisms and predicting patient outcomes.

Keywords:
autoimmune diseaseeQTLimmune cellmacrophagesmonocytesrheumatoid arthritissystemic lupus erythematosustranscriptome

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Area of Science:

  • Immunology
  • Genomics
  • Computational Biology

Background:

  • Systemic autoimmune diseases involve various immune cells, but their precise roles in autoimmunity are not fully understood.
  • Transcriptome analysis offers a dynamic view of gene expression in different cell types, complementing genomic data.

Purpose of the Study:

  • To review how transcriptome analysis enhances understanding of immune cell roles in autoimmune diseases.
  • To highlight the ImmuNexUT database and discuss experimental/analytical designs for transcriptome studies.
  • To explore the application of transcriptome data in predicting patient prognosis.

Main Methods:

  • Review of transcriptome analysis studies in autoimmune diseases.
  • Focus on single-cell RNA sequencing (scRNA-seq) for immune cell atlases.
  • Integration of genomic data with expression quantitative trait locus (eQTL) analysis.

Main Results:

  • scRNA-seq identifies specific immune cell populations, including pro-inflammatory monocytes/macrophages and distinct T and B cell subsets, in autoimmune lesions.
  • eQTL analysis helps pinpoint candidate causal genes and immune cells involved in autoimmunity.
  • Transcriptome data provides insights into the pathological functions of immune cells.

Conclusions:

  • Transcriptome analysis, particularly scRNA-seq and eQTL mapping, significantly advances the understanding of immune cell contributions to autoimmune diseases.
  • The ImmuNexUT database serves as a valuable resource for studying immune cell dynamics in autoimmunity.
  • These analyses hold potential for predicting patient prognosis and guiding therapeutic strategies.